Understanding Quality Informatics

Transcription

1 Understanding Quality Informatics

2 Background Quality measurement and reporting has traditionally relied on manual abstraction Burdensome on providers Recognition of lack of timeliness of data Meaningful Use changed the landscape Latest NPRM proposes sunsetting manually abstracted measures Creates need for a change in skill sets involved in measurement and reporting

3 Understanding Informatics American Medical Informatics Association - Biomedical informatics (BMI) is the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.* Clinical Informatics is the scientific discipline that seeks to enhance human health by implementing novel information technology, computer science and knowledge management methodologies to prevent disease, deliver more efficient and safer patient care, increase the effectiveness of translational research, and improve biomedical knowledge access.** * **

4 HIMSS-Recognized Informatics Specialties Clinical informatics Pharmacy Informatics Nursing Informatics Nutrition Informatics

5 Problem Definition Quality measurement moving to EHR-based reporting Days of manual abstraction are decreasing Regulatory environment driving heavy need for automation in calculation and reporting of quality metrics Gap in Informatics skill set focusing strictly on quality of care IT and clinical skill sets exist, but need a translator Complimentary to other Informatics specialties Reimbursement is increasingly driven off quality measure performance

6 How do we solve the problem? Proposed definition: Using, refining, and developing Health Information Technology to measure, assess, and provide feedback to guide providers in providing high quality patient care.

7 Key Attributes of the Quality Informatics Function Identify data components needed for measurement of quality metrics Interface between IT, Practice, Quality measurement experts Requirements gathering Solution brokering Turn data into information Report development Defect analysis Data interpretation Leadership and provider coaching

8 Key Roles Clinical Practice Committees IT Programmers Report developers Clinical RN, LPN or other appropriately credentialed individual to work with practice in turning data into information, coach on documentation workflows.

9 Process of Building the QIS Function Defined a job description; leveled I, II, III based on knowledge, experience Evaluated current skill set Findings: many people with expert knowledge of quality and clinical arena, few with technical expertise

10 Two-Pronged Approach Jump-started team build by hiring in individuals with the necessary skill set Working with existing individuals to educate on technical aspects to bring to necessary level of competency Long-term outlook; reallocation of skill sets to fully implement team structure

11 Results Systems Manager supervising QIS, Reporting Specialists, IT Programmers Defined team of QIS s and Reporting Specialists Dotted line reporting for IT Programmers Facilitate Enterprise Systems Manager group Participate in Administrative Oversight group

12 Work of the Team Identify data gaps for EHR-based reporting Work with measurement experts, clinical practice, IT in developing gap solutions Maintain data element dictionary and metadata for all quality metrics Facilitate meaningful scorecard builds Facilitate automation of abstraction Facilitate data standardization across the Enterprise

13 Quality Informatics Final Definition: Using, refining, and developing Health Information Technology to measure, assess, and provide feedback to guide providers in providing high quality patient care Other Benefits: Synergy between Quality Informatics Specialist and IT Synergy with other Informatics specialties Expansion to other efforts such as Patient Satisfaction More time for data interpretation and defect analysis by Quality RNs; i.e. enhanced capability to provide information rather than just data

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